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Data X:
11 14 9 19 12 17 10 17 12 15 12 20 12 15 12 19 12 15 11 15 12 19 12 16 15 20 13 18 12 15 11 14 12 20 9 16 9 16 11 16 12 10 12 19 12 19 11 16 10 15 12 18 12 17 14 19 12 17 12 14 9 19 13 20 13 19 12 16 12 15 12 16 12 18 12 16 10 15 12 17 11 14 13 20 13 19 12 13 13 16 10 16 13 18 11 18 12 16 5 17 11 19 10 16 12 19 15 13 13 16 13 13 12 12 13 17 13 17 11 17 11 16 9 16 12 14 12 16 13 13 14 16 10 14 12 20 8 12 11 18 12 14 12 19 10 18 12 14 12 18 11 15 12 14 13 17 12 19 14 13 10 19 12 18 11 20 13 15 11 15 13 15 12 20 12 15 12 19 13 18 12 18 9 15 12 17 13 12 14 18 11 19 11 20 11 13 12 17 12 16 12 18 12 18 12 14 12 15 10 12 12 17 10 14 9 18 13 17 10 17 10 20 14 16 10 14 12 15 12 18 11 20 14 17 13 17 12 17 12 15 12 17 10 18 12 17 12 20 10 15 12 16 15 18 10 15 12 18 12 20 10 19 12 14 12 16 11 15 12 17 11 18 13 20 9 17 11 18 11 15 13 16 11 11 10 15 9 18 12 17 12 16 14 19 13 18 10 15 13 17 13 19 12 18 12 19 9 16 12 16 11 16 12 14
Names of X columns:
GWSUM ITHSUM
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Omit all rows with missing values?
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yes
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R Code
if(par2=='yes') { z <- na.omit(as.data.frame(t(y))) } else { z <- as.data.frame(t(y)) } bitmap(file='test1.png') (r<-boxplot(z ,xlab=xlab,ylab=ylab,main=main,notch=TRUE,col=par1)) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Boxplot statistics',6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',1,TRUE) a<-table.element(a,'lower whisker',1,TRUE) a<-table.element(a,'lower hinge',1,TRUE) a<-table.element(a,'median',1,TRUE) a<-table.element(a,'upper hinge',1,TRUE) a<-table.element(a,'upper whisker',1,TRUE) a<-table.row.end(a) for (i in 1:length(y[,1])) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE) for (j in 1:5) { a<-table.element(a,r$stats[j,i]) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Boxplot Notches',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',1,TRUE) a<-table.element(a,'lower bound',1,TRUE) a<-table.element(a,'median',1,TRUE) a<-table.element(a,'upper bound',1,TRUE) a<-table.row.end(a) for (i in 1:length(y[,1])) { a<-table.row.start(a) a<-table.element(a,dimnames(t(x))[[2]][i],1,TRUE) a<-table.element(a,r$conf[1,i]) a<-table.element(a,r$stats[3,i]) a<-table.element(a,r$conf[2,i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab')
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Big Analytics Cloud Computing Center
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